Leveraging Future Covariates for Accurate NO2 Forecasting using Spatiotemporal Graph Neural Networks

This paper presents a novel forecasting methodology that leverages both past and future covariates, such as weather forecasts and calendar events, to accurately predict NO2 concentrations using Spatiotemporal Graph Neural Networks (STGNNs).